How Intelligent MDM Is Innovating Data Management in the Cloud

Last Published: Nov 13, 2023 |
Divya Prakash
Divya Prakash

Product Marketing Manager

From providing agility to driving innovation, master data management (MDM) brings a lot to the table. However, digital businesses like yours want more from an MDM solution than simply creating master data records for different lines of business (LOB).

In today’s world, your organization needs to be data-centric. At the same time, you probably want a modern cloud experience that drives the adoption of newer technologies and increases productivity. On top of that, you are likely looking for a comprehensive data management solution that can find your master data sets across the enterprise, understand data context by uncovering metadata, integrate master data across multiple domains, onboard new data sources for mastering and democratize trusted data to your data stakeholders. A solution that ultimately helps accelerate your business outcomes through quick deployment and reduces the total cost of ownership.

You may also be looking for automation and artificial intelligence (AI) to be embedded in each of these tasks, which can ease your configuration processes, apply learnings quickly, reduce the resources required to perform manual tasks and shorten your time to value dramatically. To summarize, you need data intelligence which allows you to generate AI-powered insights that help improve productivity, achieve operational efficiency and enhance customer experience.

Will a Traditional MDM Tool Cater to the Needs of Modern Enterprises? 

The short answer is: no. You need a modern, AI-powered MDM solution that is scalable, modular and intelligent to resolve data issues effectively. An advanced cloud data management solution will allow you to deliver trusted insights that your business stakeholders can effectively leverage and use to respond to ever-changing market conditions. Because it is built on a microservices architecture, an intelligent MDM solution is able to use AI to automate and scale data mastering across multiple domains.

When evaluating an intelligent MDM solution, what traits should you look for? Below are five key elements that make up the DNA of an intelligent MDM solution to deliver the data intelligence you need today.

1. Govern master data

For most enterprises, master data continuously changes as the business evolves. So, master data management cannot be treated as a one-time project. As master data changes, you need a robust governance framework to ensure your master data is of high quality and fit for use by your data consumers. Enforcing master data policies organization-wide can help you stay compliant with internal standards and external regulations.

Here are some key data capabilities that rely on master data being governed:

  • Data integration and replication: These techniques can automatically update your master data with the latest information to keep it timely. Bulk, batch and real-time integration of your MDM applications with a heterogenous set of data sources provide quick onboarding of datasets into your MDM application. An AI-driven master data solution can significantly reduce the onboarding time of your master data by automating the master data integration and mapping process. By leveraging named entity recognition and natural language understanding to identify fields (i.e., street) and field types (i.e., address), a master data solution speeds up the integration and maps the entity attributes to the data model attributes within the MDM application.
  • Data quality monitoring: This helps you ensure that master data is accurate, complete, consistent and free of data issues. Automated profiling, parsing and validation can quickly uncover the health of your data. Leveraging machine learning (ML) techniques, you can associate data quality rules with master data fields and automate the execution to cleanse, standardize and enrich the master data sets. Further, blended ML techniques (e.g., deterministic, heuristic and probabilistic) can rapidly detect and rectify data inconsistencies in master data records, such as data accuracy, completeness and duplicates.
  • AI-powered data discovery: This helps you identify and classify sensitive and personal data sitting across multiple cloud and on-premises data sources. You can use data discovery as an attribute of master data to better understand how you should use your data. AI and ML techniques like clustering, data similarity and semantic tagging can automate master data discovery and domain identification to source relevant master data entities across the enterprise data landscape.
  • Data lineage: This can help you uncover data integrity issues by tracking and auditing changes made to your master data. Data lineage provides a full audit trail of changes, including who made them, what was changed and when it happened. This helps build the data trust you need to effectively initiate your data analytics and data science use cases. Leveraging ML techniques — like pattern recognition, data tagging and classification — with real-time monitoring and alerts can accelerate the time to value for your data consumers by quickly identifying and resolving potential data issues.
  • Policy-based privacy and access controls: The application of these controls can be automated from within your MDM application for advanced master data governance. Access controls can be enforced according to the policies and user authorizations you set, and master data can be dynamically masked at the time of a query. This enables organizations to meet privacy standards in MDM use cases, such as personalizing compliance, enriching customer profiles and enabling the broader use of customer data.

2. Democratize master data

You likely store master data related to multiple domains, such as customer, product, etc. Different LOB owners leverage this master data to drive business value relevant to their area. For example, your marketing team may plan to drive revenue growth by using customer and product data to improve marketing analytics. At the same time, your operations team might be working on optimizing costs by leveraging material and supplier data to improve procurement analytics.

Broad and consistent use of master data throughout your organization can improve analytics, operations and decision-making. However, often master data is not readily available to LOB data consumers. In some cases, searching for the relevant data a significant amount of time, whereas in others, IT may become a bottleneck as they address requests one at a time.

That’s where self-service access to master data through a data marketplace comes in. With a data marketplace, you can provide your data users with a seamless and transparent “shopping experience” from data request to data delivery. You can apply data usage terms and conditions based on the type of master data being accessed to guide your data consumers on how to use sensitive and personal information compliantly and ethically.

An AI-enabled data marketplace solution can leverage content-based filtering, user ranking and data similarity to automatically recommend the best master data assets for your specific use case. It can also help with last mile delivery by provisioning the required data to your choice of destination. The marketplace solution can be deployed on top of your existing data landscape to make that landscape more accessible to less technical users or those with lower data literacy.

3. Deliver efficient data products

You can use advanced, AI-driven MDM to enhance the quality and utility of your data products, making them more valuable to your users.

Different business units may have varying priorities, such as improving the customer experience, streamlining business processes, complying with regulations, growing revenues or cutting costs, introducing new products faster or optimizing supply chains. Successful execution of these use cases relies on access to trustworthy and ready-to-use, relevant data.

Prebuilt cloud-native 360 applications can be used to curate, enrich and transform your master data into valuable data products for your most common domains, such as customer, product, supplier and reference data. To suit your business requirements, these data products can be easily extended and customized by adding entities to the data model. With 360 applications, you can also create custom data models according to your business needs.

For example, AI-powered MDM tools can quickly add and map to new data sources for common data types, such as addresses, phone numbers and emails. You can easily manage the aspects of data modeling from a single pane of glass using an intuitive model configuration screen. Complemented by capabilities like reference data modeling, this solution leverages core AI capabilities and can deploy a new domain in weeks instead of months.

4. Use pre-built extensions

A simplified and accelerated MDM implementation enables you to deliver business value faster and stay competitive. Pre-built extensions are ready-to-use packages that can fast-track your MDM implementation by providing specialized features to address the specific needs of your data management strategy. 

Extensions can include additional business entities, related data model attributes, reference data, relationships, pre-defined batch jobs, additional data quality rules and data integration assets to easily connect to multiple data sources. You can even customize these extensions to add or remove data model attributes for a particular business entity.

Let’s see this in action. The first step to mastering data records in an MDM solution is to connect to various master data sources and bring your data into the MDM solution. Integration extensions can enable you to create mapping tasks and task-flows to import data assets from source systems and process your records in the MDM application.  records in the MDM application.

Similarly, industry extensions can accelerate an industry-specific MDM implementation. For example, a healthcare extension can help you better manage data by creating additional data model attributes for business entities relevant to the healthcare industry, like payers and providers. It can also uncover hidden relationships among them.

These pre-built extensions can be equipped with advanced AI capabilities to enrich and improve the accuracy of 360 views for your customers, products, suppliers and other domains. The blending of declarative and AI rules can accelerate training and improve the matching accuracy of these applications.

5. Leverage multidomain MDM

Today’s digital business requires a 360-degree view of your entire business that includes the relationships between multiple domains of master data, such as customer, product, supplier, location and more. For example, looking at product data in conjunction with customer data is crucial to targeting your customers with the right set of products and increasing conversion.

A multidomain MDM solution supports a variety of master data domains, implementation styles and use cases — in the cloud or on-premises. This can provide a single shared view of data across functions and support data mastering beyond customer and product domains in a single MDM solution. Apart from uncovering the hidden relationships between your different data domains, a multidomain MDM solution can be extended to support your future domain requirements.

A multidomain MDM solution leverages AI techniques, such as column signature analysis, to identify primary and unique keys as well as infer relationships and joins across master data entities. These insights can help automate the creation of a cross-domain, cross-department, master data knowledge graph, which simplifies navigation and helps with analysis to determine opportunities for cross-sell and product substitutions.

Next Steps

Intelligent MDM solutions will enable your enterprise to be AI-ready. Serving as the backbone of AI-readiness, implementing an intelligent MDM solution is critical as you embark on your data management and AI journey.

Informatica Intelligent MDM SaaS, a service of the Informatica Intelligent Data Management Cloud (IDMC), is a modern and all-in-one MDM solution using a cloud-native microservices architecture delivered with user-centric design principles and AI-powered automation through the CLAIRE AI engine. Learn more about how you can bring business agility, improve your organization’s productivity and accelerate your business outcomes with the Informatica intelligent MDM solution.

First Published: Nov 13, 2023